Volume 31 Issue 6
Dec.  2025
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Article Navigation >  Journal of Geomechanics  > 2025  >  31(6): 1188-1209
WANG C H，LI W，2025. Major advances and prospects in in-situ stress measurement and estimation methods over the past 10 years (2014–2025）[J]. Journal of Geomechanics，31（6）：1188−1209 doi: 10.12090/j.issn.1006-6616.2025080
Citation: WANG C H，LI W，2025. Major advances and prospects in in-situ stress measurement and estimation methods over the past 10 years (2014–2025）[J]. Journal of Geomechanics，31（6）：1188−1209 doi: 10.12090/j.issn.1006-6616.2025080
shu

Major advances and prospects in in-situ stress measurement and estimation methods over the past 10 years (2014–2025）

doi: 10.12090/j.issn.1006-6616.2025080

  • National Institute of Natural Hazards, Ministry of Emergency Management, Beijing 100085, China

Funds:  This research is financially supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 42404111).
More Information
  • Received: 2025-07-04
  • Revised: 2025-10-20
  • Accepted: 2025-10-27
    • Available Online: 2025-12-03
  • Published: 2025-12-28
    Abstract
  •   Objective  The characteristics of the in-situ stress field are fundamental to major strategic underground engineering projects, deep earth resource and energy development, and geohazard prevention and control. Over the past decade, significant progress and breakthroughs have been made in in-situ stress measurement and estimation methods.   Method  This article systematically reviews the main advances in in-situ stress measurement and estimation methods from 2014 to 2025. These advances can be categorized into four technical fields: core-based methods, borehole-based methods, geophysics-based methods, and emerging data-driven estimation methods.   Results  Core-based testing methods have improved the accuracy of in-situ stress magnitude measurements through theoretical refinements and enhanced the precision of stress direction determination through equipment upgrades, addressing the previous inability to measure in-situ stress in low-strength rocks. Borehole-based testing methods have been further developed and now use sensors with high temperature and pressure resistance, as well as corrosion resistance, enabling deep borehole imaging, direction identification, and in-situ stress measurement. Accurate analytical solutions for in-situ stress magnitudes have been obtained through corrections. Geophysics-based methods have enabled the inversion of the in-situ stress field using focal mechanism solutions of minor earthquakes (magnitude 0.5–1.0), providing extensive rock mass stress information. Acoustic, imaging, and dipmeter logging technologies have also evolved to utilize non-contact, high-precision, and high-sensitivity equipment, making them more suitable for deep boreholes and oilfield development. Advancements in big data and artificial intelligence have given rise to data-driven testing methods that can be divided into three categories based on prediction approaches: machine learning, intelligent neural network prediction, and intelligent back-analysis. These methods have advanced in-situ stress measurement from discrete "point measurements" to full-field "field reconstruction."   Conclusion  Compared to traditional methods, current in-situ stress testing is moving toward "deepening, intelligentization, and systematization."   Significance  Future research should focus on the dual drivers of intelligent prediction models and intelligent testing equipment to address the challenges of complex deep geological environments.

     

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